XWeB: the XML Warehouse Benchmark

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems

Planning effort as an effective risk management tool

In project management, high levels of risk are considered to be a significant obstacle for project success. This paper investigates whether improving the project plan can lead to improved success for high-risk projects. A quality of planning index was designed to explore how the presence of high risk affects the quality of planning and project success. The index includes managerial aspects such as costs, human resources, procurement and quality, as well as organizational support aspects based on organization maturity models. In a field study based on data collected from 202 project managers regarding their most recent projects, it was found that the levels of risk at the beginning of projects has no effect on their final success. Drilling down to find an explanation for this surprising phenomenon, we found that in the presence of high risk, project managers significantly improve their project plans. Hence, in high-risk projects, better project plans improve all four dimensions of project success: schedule overrun, cost overrun, technical performance and customer satisfaction. However, in low-risk projects, better project plans did not contribute to reducing schedule or cost overruns. In other words, while endless risk management tools are developed, we found that improving the project plan is a more effective managerial tool in dealing with high-risk projects. Finally, the paper presents the most common planning tools currently being used in high-risk projects

Student Engagement in Law School: Preparing 21st Century Lawyers

Presents findings from an annual survey, with a focus on teaching and learning methods that help students develop as ethical professionals and improve their legal writing and problem-solving skills

Bringing Human Factor to Business Intelligence

Trabalho apresentado em 11th INEKA Conference, 11-13 junho 2019, Verona, ItáliaStarting from Business Intelligence (BI) reference models, this work proposes to extend the multi-dimensional data modeling approach to integrate Human Factors (HF) related dimensions. The overall goal is to promote a fine grain understanding of derived Key Performance Indicators (KPIs) through an enhanced characterization of the operational level of work context. HF research has traditionally approached critical domains and complex socio-technical systems with a chief consideration of human situated action. Grounded on a review of the body of knowledge of the HF field this work proposes the Business Intelligence for Human Factors (BI4HF) framework. It intends to provide guidance on pertinent data identification, collection methods, modeling and integration within a BI project endeavor. BI4HF foundations are introduced and a use case on a manufacturing industry organization is presented. The outcome of the enacted BI project referred in the use case allowed new analytical capabilities regarding newly derived and existing KPIs related to operational performance.N/

Software Engineering Methods for the Internet of Things: A Comparative Review

Accessing different physical objects at any time from anywhere through wireless network heavily impacts the living style of societies worldwide nowadays. Thus, the Internet of Things has now become a hot emerging paradigm in computing environments. Issues like interoperability, software reusability, and platform independence of those physical objects are considered the main current challenges. This raises the need for appropriate software engineering approaches to develop effective and efficient IoT applications software. This paper studies the state of the art of design and development methodologies for IoT software. The aim is to study how proposed approaches have been solved issues of interoperability, reusability, and independence of the platform. A comparative study is presented for the different software engineering methods used for the Internet of Things. Finally, the key research gaps and open issues are highlighted as future directions

자동차 사양 변경을 실시간 반영하는 데이터 기반 디자인 접근 방법

학위논문 (박사) -- 서울대학교 대학원 : 융합과학기술대학원 융합과학부(지능형융합시스템전공), 2020. 8. 곽노준.The automotive industry is entering a new phase in response to changes in the external environment through the expansion of eco-friendly electric/hydrogen vehicles and the simplification of modules during the manufacturing process. However, in the existing automotive industry, conflicts between structured production guidelines and various stake-holders, who are aligned with periodic production plans, can be problematic. For example, if there is a sudden need to change either production parts or situation-specific designs, it is often difficult for designers to reflect those requirements within the preexisting guidelines. Automotive design includes comprehensive processes that represent the philosophy and ideology of a vehicle, and seeks to derive maximum value from the vehicle specifications. In this study, a system that displays information on parts/module components necessary for real-time design was proposed. Designers will be able to use this system in automotive design processes, based on data from various sources. By applying the system, three channels of information provision were established. These channels will aid in the replacement of specific component parts if an unexpected external problem occurs during the design process, and will help in understanding and using the components in advance. The first approach is to visualize real-time data aggregation in automobile factories using Google Analytics, and to reflect these in self-growing characters to be provided to designers. Through this, it is possible to check production and quality status data in real time without the use of complicated labor resources such as command centers. The second approach is to configure the data flow to be able to recognize and analyze the surrounding situation. This is done by applying the vehicles camera to the CCTV in the inventory and distribution center, as well as the direction inside the vehicle. Therefore, it is possible to identify and record the parts resources and real-time delivery status from the internal camera function without hesitation from existing stakeholders. The final approach is to supply real-time databases of vehicle parts at the site of an accident for on-site repair, using a public API and sensor-based IoT. This allows the designer to obtain information on the behavior of parts to be replaced after accidents involving light contact, so that it can be reflected in the design of the vehicle. The advantage of using these three information channels is that designers can accurately understand and reflect the modules and components that are brought in during the automotive design process. In order to easily compose the interface for the purpose of providing information, the information coming from the three channels is displayed in their respective, case-specific color in the CAD software that designers use in the automobile development process. Its eye tracking usability evaluation makes it easy for business designers to use as well. The improved evaluation process including usability test is also included in this study. The impact of the research is both dashboard application and CAD system as well as data systems from case studies are currently reflected to the design ecosystem of the motors group.자동차 산업은 친환경 전기/수소 자동차의 확대와 제조 공정에서의 모듈 단순화를 통해서 외부 환경의 변화에 따른 새로운 국면을 맞이하고 있다. 하지만 기존의 자동차 산업에서 구조화된 생산 가이드라인과 기간 단위 생산 계획에 맞춰진 여러 이해관계자들과의 갈등은 변화에 대응하는 방안이 관성과 부딪히는 문제로 나타날 수 있다. 예를 들어, 갑작스럽게 생산에 필요한 부품을 변경해야 하거나 특정 상황에 적용되는 디자인을 변경할 경우, 주어진 가이드라인에 따라 디자이너가 직접 의견을 반영하기 어려운 경우가 많다. 자동차 디자인은 차종의 철학과 이념을 나타내고 해당 차량제원으로 최대의 가치를 끌어내고자 하는 종합적인 과정이다. 본 연구에서는 여러 원천의 데이터를 기반으로 자동차 디자인 과정에서 활용할 수 있도록 디자인에 필요한 부품/모듈 구성요소들에 대한 정보를 실시간으로 표시해주는 시스템을 고안하였다. 이를 적용하여 자동차 디자인 과정에서 예상 못한 외부 문제가 발생했을 때 선택할 구성 부품을 대체하거나 사전에 해당 부품을 이해하고 디자인에 활용할 수 있도록 세 가지 정보 제공 채널을 구성하였다. 첫 번째는 자동차 공장 내 실시간 데이터 집계를 Google Analytics를 활용하여 시각화하고, 이를 공장 자체의 자가 성장 캐릭터에 반영하여 디자이너에게 제공하는 방식이다. 이를 통해 종합상황실 등의 복잡한 인력 체계 없이도 생산 및 품질 현황 데이터를 실시간으로 확인 가능하도록 하였다. 두 번째는 차량용 주차보조 센서 카메라를 차량 부착 뿐만 아니라 인벤토리와 물류센터의 CCTV에도 적용하여 주변상황을 인식하고 분석할 수 있도록 구성하였다. 차량의 조립 생산 단계에서 부품 단위의 이동, 운송, 출하를 거쳐 완성차의 주행 단계에 이르기까지 데이터 흐름을 파악하는 것이 디자인 부문에 필요한 정보를 제공할 수 있는 방법으로 활용되었다. 이를 통해 기존 이해관계자들의 큰 반발 없이 내부의 카메라 기능으로부터 부품 리소스와 운송 상태를 실시간 파악 및 기록 가능하도록 하였다. 마지막으로 공공 API와 센서 기반의 사물인터넷을 활용해서 도로 위 차량 사고가 발생한 위치에서의 현장 수리를 위한 차량 부품 즉시 수급 및 데이터베이스화 방법도 개발 되었다. 이는 디자이너로 하여금 가벼운 접촉 사고에서의 부품 교체 행태에 대한 정보를 얻게 하여 차량의 디자인에 반영 가능하도록 하였다. 시나리오를 바탕으로 이 세 가지 정보 제공 채널을 활용할 경우, 자동차 디자인 과정에서 불러들여오는 부품 및 모듈의 구성 요소들을 디자이너가 정확히 알고 반영할 수 있다는 장점이 부각되었다. 정보 제공의 인터페이스를 쉽게 구성하기 위해서, 실제로 디자이너들이 자동차 개발 과정에서 디자인 프로세스 상에서 활용하는 CAD software에 세 가지 채널들로부터 들어오는 정보를 사례별 컬러로 표시하고, 이를 시선추적 사용성 평가를 통해 현업 디자이너들이 사용하기 쉽게 개선한 과정도 본 연구에 포함시켜 설명하였다.1 Introduction 1 1.1 Research Background 1 1.2 Objective and Scope 2 1.3 Environmental Changes 3 1.4 Research Method 3 1.4.1 Causal Inference with Graphical Model 3 1.4.2 Design Thinking Methodology with Co-Evolution 4 1.4.3 Required Resources 4 1.5 Research Flow 4 2 Data-driven Design 7 2.1 Big Data and Data Management 6 2.1.1 Artificial Intelligence and Data Economy 6 2.1.2 API (Application Programming Interface) 7 2.1.3 AI driven Data Management for Designer 7 2.2 Datatype from Automotive Industry 8 2.2.1 Data-driven Management in Automotive Industry 8 2.2.2 Automotive Parts Case Studies 8 2.2.3 Parameter for Generative Design 9 2.3 Examples of Data-driven Design 9 2.3.1 Responsive-reactive 9 2.3.2 Dynamic Document Design 9 2.3.3 Insignts from Data-driven Design 10 3 Benchmark of Data-driven Automotive Design 12 3.1 Method of Global Benchmarking 11 3.2 Automotive Design 11 3.2.1 HMI Design and UI/UX 11 3.2.2 Hardware Design 12 3.2.3 Software Design 12 3.2.4 Convergence Design Process Model 13 3.3 Component Design Management 14 4 Vehicle Specification Design in Mobility Industry 16 4.1 Definition of Vehicle Specification 16 4.2 Field Study 17 4.3 Hypothesis 18 5 Three Preliminary Practical Case Studies for Vehicle Specification to Datadriven 21 5.1 Production Level 31 5.1.1 Background and Input 31 5.1.2 Data Process from Inventory to Designer 41 5.1.3 Output to Designer 51 5.2 Delivery Level 61 5.2.1 Background and Input 61 5.2.2 Data Process from Inventory to Designer 71 5.2.3 Output to Designer 81 5.3 Consumer Level 91 5.3.1 Background and Input 91 5.3.2 Data Process from Inventory to Designer 101 5.3.3 Output to Designer 111 6 Two Applications for Vehicle Designer 86 6.1 Real-time Dashboard DB for Decision Making 123 6.1.1 Searchable Infographic as a Designer's Tool 123 6.1.2 Scope and Method 123 6.1.3 Implementation 123 6.1.4 Result 124 6.1.5 Evaluation 124 6.1.6 Summary 124 6.2 Application to CAD for vehicle designer 124 6.2.1 CAD as a Designer's Tool 124 6.2.2 Scope and Method 125 6.2.3 Implementation and the Display of the CAD Software 125 6.2.4 Result 125 6.2.5 Evaluation: Usability Test with Eyetracking 126 6.2.6 Summary 128 7 Conclusion 96 7.1 Summary of Case Studies and Application Release 129 7.2 Impact of the Research 130 7.3 Further Study 131Docto

Evaluating the quality of project planning: a model and field results

Faulty planning will result in project failure, whereas high-quality project planning increases the project's chances of success. The paper reports on the successful development and implementation of a model aimed at evaluating the quality of project planning. The model is based on both the abilities required of the project manager and the organizational support required for a proper project management infrastructure. The model was validated and applied by 282 project managers in nine organizations, where strong and weak planning processes were identified and analysed

Employing Data Warehousing for Contract Administration: e-Dispute Resolution Prototype

Although data warehouse is very practical for decision making, its application in contract administration is rather limited because of the complicated legal issues and the voluminous data involved. This research attempts to bridge this gap in two ways. First, conceptual models of data warehouse are developed to explain the contents and overall features of the system that were verified by 12 experts in Malaysia. Second, an electronic dispute resolution template, known as e-Dispute Resolution (e-DR), is prototyped by using a database tool based on the guidelines of contractual variations agreed by the experts. Subsequently, the prototype is evaluated by 16 professional quantity surveyors from an established consulting firm. The prototype was organized based on a systematic breakdown of issues and incorporated a Boolean keyword search feature. The results show that the concept of data warehouse is applicable to contract administration and is well received by practitioners. Overall, this article renders significant theoretical and practical contributions in which the resulting e-DR does not only lead toward more informed decision making but is also able to mitigate or prevent contractual disputes in the construction industry, where such a phenomenon seems to be inevitabl

BioWarehouse: a bioinformatics database warehouse toolkit

BACKGROUND: This article addresses the problem of interoperation of heterogeneous bioinformatics databases. RESULTS: We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. CONCLUSION: BioWarehouse embodies significant progress on the database integration problem for bioinformatics